Figure 2 | Scientific Reports

Figure 2

From: A showcase study on personalized in silico drug response prediction based on the genetic landscape of muscle invasive bladder cancer

Figure 2

Filtering shows distinct effects on the SNV/CNV selection. (a) Barplot illustrates the log-scaled mutation load per sample for non-synonymous mutations, before (blue bars) and after (red bars) filtering for provided drug-gene interactions. Bars are overlying, not stacked. (b) Boxplots depict the distribution of SNV types after filtering for drug-related variants. (c) The barplot shows the differences of CNV load per sample throughout filtering. The overlying bars represent CNV load before (blue bars) and after (red bars) filtering for non-curated drug-gene interactions. (d) Boxplots illustrate the distribution of CNV types across TCGA-BLCA samples after filtering for drug-related CNVs (DEL deletion, 0 copies; LOSS copy number loss, 1 copy; GAIN copy number gain, 3–4 copies; AMP amplification, > 4 copies). (R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/)57.

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